Efficiency nonminimally supported design for three parameters weighted exponential model

Abstract

Abstract The weighted exponential distribution function has a specific curve shape, the curve from zero reaches to the maximum point then down, and at a certain time it is relatively constant tends to zero. This function can be used to describe the growth curve model. Minimally supported design is a design with the number of supported design equal to the number of parameters in the model. Locally D-optimal design for the weighted exponential model is minimally supported design with uniform weight. The standardized variance of D-optimal design is less than or equal to the number of parameters and maximized the standardized variance at the supported designs. We propose an alternative design by adding one supported design. Nonminimally supported design is obtained from supported design of D-optimal design plus one supported design in three ways, by adding one of them, by adding the average of them or by adding one supported design around them. We compare nonminimally supported designs in terms of efficiency, standardized variance, and propose a design that is efficient and practically convenient for practitioners.